An improved dehazing algorithm using muti-scale weighted transmission fusion and self-adaptive gamma correction

Aiming at the problems of image distortion and detail information loss occurring in recent dehazing algorithms, this paper proposes a dehazing algorithm based on dark channel prior with multi-scale weighted transmission fusion and self-adaptive gamma correction. Firstly, in order to refine the transmission map, a multi-scale weighted transmission fusion strategy with three scales is applied in the transmission estimation step. Then, a self-adaptive gamma correction method is proposed to enhance the contrast performance after applying the multi-scale weighted transmission fusion to image dehazing, and finally get the desired dehazed image. Experimental results demonstrated that the proposed algorithm can not only overcome the problems of image distortion and detail information loss well, but also yields a satisfied performance in comparison with tested similar methods.